RRepoGEO

REPOGEO REPORT · LITE

boson-ai/higgs-audio

Default branch main · commit 05a145bb · scanned 6/25/2026, 5:27:45 AM

GitHub: 8,240 stars · 634 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface boson-ai/higgs-audio, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Clarify the repo's legacy status and purpose in the About description

    Why:

    CURRENT
    Text-audio foundation model from Boson AI
    COPY-PASTE FIX
    Legacy repository for Higgs Audio v2. This repo is no longer actively maintained; please see Higgs Audio v3 for the latest model and API.
  • mediumhomepage#2
    Set the homepage URL to the official Higgs Audio v3 documentation

    Why:

    COPY-PASTE FIX
    https://docs.boson.ai/models/higgs-audio-tts

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface boson-ai/higgs-audio
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ElevenLabs
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ElevenLabs · recommended 1×
  2. Descript (with Overdub) · recommended 1×
  3. Resemble.ai · recommended 1×
  4. WellSaid Labs · recommended 1×
  5. Google Cloud Text-to-Speech (with Custom Voice) · recommended 1×
  • CATEGORY QUERY
    How to generate realistic speech from text with custom voices and emotion control?
    you: not recommended
    AI recommended (in order):
    1. ElevenLabs
    2. Descript (with Overdub)
    3. Resemble.ai
    4. WellSaid Labs
    5. Google Cloud Text-to-Speech (with Custom Voice)
    6. Amazon Polly (with Custom Voice)

    AI recommended 6 alternatives but never named boson-ai/higgs-audio. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are options for self-hosting a multilingual text-to-speech model for production?
    you: not recommended
    AI recommended (in order):
    1. Coqui TTS (coqui-ai/TTS)
    2. ESPnet (espnet/espnet)
    3. OpenVINO (openvinotoolkit/openvino)
    4. NVIDIA Riva (nvidia/riva)
    5. MaryTTS (marytts/marytts)
    6. TensorFlow TTS (TensorFlow/Text-to-Speech)
    7. Fairseq (facebookresearch/fairseq)

    AI recommended 7 alternatives but never named boson-ai/higgs-audio. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of boson-ai/higgs-audio?
    pass
    AI did not name boson-ai/higgs-audio — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts boson-ai/higgs-audio in production, what risks or prerequisites should they evaluate first?
    pass
    AI named boson-ai/higgs-audio explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo boson-ai/higgs-audio solve, and who is the primary audience?
    pass
    AI named boson-ai/higgs-audio explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of boson-ai/higgs-audio. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/boson-ai/higgs-audio.svg)](https://repogeo.com/en/r/boson-ai/higgs-audio)
HTML
<a href="https://repogeo.com/en/r/boson-ai/higgs-audio"><img src="https://repogeo.com/badge/boson-ai/higgs-audio.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

boson-ai/higgs-audio — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite